Earlier this year, the South Big Data Hub partnered with Microsoft Research to offer researchers in the South Hub region the opportunity to apply for cloud credits on Azure, the comprehensive cloud services platform offered through Microsoft. The opportunity was designed to provide cloud computing resources to support data-intensive research projects.
Applications were due August 16 and in November, Microsoft announced that eight researchers at institutions within the South Hub region will receive Azure credits. The researchers will also be able to take advantage of Azure services and tools to efficiently drive insights from data-driven research.
Research projects that will take advantage of the Azure credits include an effort to use Twitter data to develop a model that predicts public sentiment toward police over time (Graham MacDonald, Urban Institute); development of a compute-intensive graph mining system that divides graph mining jobs into individual tasks (Da Yan, University of Alabama at Birmingham); a project to build and test deep learning models for analysis of mobile text that measures covariates related health outcomes, such as trust, literacy, and anxiety (Ahmed Abbasi, University of Virginia), and an effort to develop a cloud-agnostic, large-scale data analytics framework (Claris Castillo, RENCI).
Projects from any discipline were considered for the awards, as long as the submission clearly articulated the data that the proposed research relied on, and the Azure-based analytics services that would be used.
Congratulations to all the South Big Data Hub Awardees:
- Prashanti Manda, assistant professor, department of computer science, University of North Carolina at Greensboro.
- Lisa Singh, professor, department of computer science, Georgetown University.
- Graham MacDonald, data scientist and senior manager for data technology and innovation, The Urban Institute.
- Ragib Hasan, associate professor, department of computer and information sciences, University of Alabama at Birmingham.
- Ahmed Abbasi, Murray Research Professor and director, Center for Business Analytics, University of Virginia.
- Da Yan, assistant professor, department of computer and information sciences, University of Alabama at Birmingham.
- John Craft, research assistant professor, department of biology and biochemistry, University of Houston.
- Claris Castillo, senior computational and networked systems researcher, RENCI, University of North Carolina at Chapel Hill.
Negotiating the Digital and Data Divide Workshop builds momentum for the series “Keeping Data Science Broad.”
Participants of the Negotiating the Digital and Data Divide Workshop, in front of the wall of challenges and visions used to collect ideas on the future of data science education.
This month, participants from universities across the nation, community colleges, tribal colleges, minority-serving institutions, nonprofits, and industry joined forces with the South Big Data Hub and Georgia Tech to confront the challenges of building data science capacity through traditional and alternative educational practices. Organized by Dr. Renata Rawlings-Goss, a co-executive director of the South Big Data Hub, the two-day workshop, sponsored by multiple directorates within the National Science Foundation, brought together a diverse mix of participants to navigate the complex issues of reforming data science education to prepare for the data-driven workforce of the future.
NSF’s Wendy Nilsen speaking at a South Big Data Hub Roundtable.
Each day countless devices—from monitors in hospitals to diagnostic tests to Fitbits—capture huge amounts of health data. That data could change how patients and doctors interact, how diseases are diagnosed and treated, and the amount of control individuals have over their health outcomes.
But there’s a catch, says Wendy Nilsen, PhD, program director of the Smart and Connected Health Initiative at the National Science Foundation.
The data is plentiful, Nilsen acknowledged. The challenge, she said, is how to make that data easier to use, how to standardize it so it can be analyzed, how to scale it, keep it safe, and how to account for external factors such as the environment or a person’s genome.
Nilsen discussed these challenges and how to address them in a roundtable discussion hosted by the South Big Data Hub on October 14. Nilsen’s talk, titled “Smart Health and Our Future” provides an overview of the challenges that must be addressed as well as the ultimate goal: A system where patients use data to take more control of their health and where healthcare practitioners can use data from multiple sources to improve diagnoses and health outcomes.
To view the presentation slides, click here.
On August 28, Karl Schmitt, PhD, an assistant professor in the department of mathematics and statistics at Valparaiso University, attended the webinar Data Science Education in Traditional Contexts, hosted by the South Big Data Innovation Hub as part of its Keeping Data Science Broad: Bridging the Data Divide series. The webinar featured five speakers, including Schmitt, who is also the director of data sciences at Valparaiso. Each speaker talked about their own programs and experiences in data science education as well as some of the challenges involved in creating and implementing educational programs in a field that is still very new and in the process of being defined. Continue reading
By Eun Kyong Shin
The 2017 International Conference on Social Computing, Behavioral-Cultural Modeling, & Prediction and Behavior Representation in Modeling and Simulation (SBP-BRiMS 2017) was held in Washington, DC, in July, and prominent fields applying social computing techniques include public health and healthcare. In early modern epidemiology, data collection processes relied heavily on painstaking manual labor. Data on a large scale was hard to obtain and resulted from careful observation and intensive recording. Since the introduction of the internet and advances in digital communication, massive amounts of dynamic data have accumulated exponentially. Along with the digitization of medical practices and other social data collection process, the nature of scientific discovery has been fundamentally changed. Continue reading
Panelists discuss data visualization at a recent workshop sponsored by the South and West Big Data Hubs.
By Mark Schroeder
Throughout human history, stories have helped us make sense of sequences of events in our lives, infer cause and effect relationships, and share them with others. Just as our own memories are fallible and retelling stories can shape how we remember events, data can be fallible too. Its value is shaped by the process used to collect it and can be incomplete, incorrect, or biased in some fashion. How can we use data to gain true insights about the world and share them despite these challenges?
The American Association for Advancement of Science (AAAS) Science & Technology Policy Fellowship Big Data Affinity Group, in collaboration with the South Big Data Hub, West Big Data Hub, and The National Consortium for Data Science, are making this Friday’s data visualization and storytelling event available for virtual attendees. To learn more about the event, visit the website or read our earlier blog post announcing the event.
Data-Driven Storytelling: A Deep Dive into Visualization Techniques
July 14 | 9:00 AM – Noon ET | WebCast
Join the Webcast: http://bit.ly/datavizwebex
Event Number: 641 886 660 | Event password: dataviz
Attendees at the mHealth conference discuss key issues, including mHealth standards, at a breakout session.
By Alex Cheng
I was honored to have the opportunity to attend the Mobile Health (mHealth) conference sponsored by the South Big Data Innovation Hub and the National Consortium for Data Science as a third-year graduate student in biomedical informatics at Vanderbilt University. My research focuses on using mHealth technology to improve the efficiency of outpatient clinic operations and the quality of care for patients. Continue reading
Reflections on the South BD Hub mHealth Workshop
By Chenzhang Bao
In recent years, mobile health (mHealth) has become one of the most popular health care movements for patients and providers. Consumers have embraced the use of mHealth applications in their daily lives through wearable devices, and use these apps to monitor their exercise routines, heartbeats, and sleep quality. The use of mHealth apps is critical for research into new mechanisms designed to improve the quality of patient engagement; a factor that has previously been hard to measure or even unobservable to providers. One important research question looks at the relationship between patients’ usage of mHealth devices, their engagement in their own health and the future health outcomes. Continue reading
When we launched the Big Data Innovation Hubs at the end of 2015, we could never have imagined that our mission of “breaking barriers, bridging solutions, and accelerating partnerships,” intense but rewarding work, would yield over 800 members—many of whom actively contribute to Hub communities of practice, dozens of productive partnerships, several funded new projects, and nearly 20 workshops. A year and a half later, on Friday, June 9, 2017, more than 75 people from across sectors and disciplines—academia, government, nonprofits, and industry—met at the Microsoft Chevy Chase Pavilion near Washington, DC, to assess the progress of the South Big Data Hub, and shape its future. It was a day of catching up on current efforts (some of which began at the first all-hands hub meeting), and sparking new collaborations.